Removed a mistake by Yi Xiong for setting problematic threshold param…

…eter in unicox analysis

DESCRIPTION

@@ -72,4 +72,4 @@ VignetteBuilder:
 Encoding: UTF-8
 LazyData: true
 Roxygen: list(markdown = TRUE)
-RoxygenNote: 7.2.3
+RoxygenNote: 7.3.1

NEWS.md

@@ -3,7 +3,8 @@
 - Added gene and pathway cross-omics analysis functions/modules.
 - Added `app_run2()` function for custom app start with lightweight modules.
 - Fixed `pdf()` parameter for KM plot
-- Improve the UI of Custom TPC Modules.
+- Improved the UI of Custom TPC Modules.
+- Removed a mistake by Yi Xiong for setting problematic threshold parameter in unicox analysis.
 
 # UCSCXenaShiny 2.1.0
 

R/vis_pancan_value.R

@@ -219,7 +219,6 @@ vis_toil_TvsN <- function(Gene = "TP53", Mode = c("Boxplot", "Violinplot"),
 #'
 #' @inheritParams vis_toil_TvsN
 #' @param measure a survival measure, e.g. "OS".
-#' @param threshold a expression cutoff, `0.5` for median.
 #' @param data_type choose gene profile type, including "mRNA","transcript","methylation","miRNA","protein","cnv"
 #' @return a `ggplot` object
 #' @examples
@@ -228,7 +227,7 @@ vis_toil_TvsN <- function(Gene = "TP53", Mode = c("Boxplot", "Violinplot"),
 #' }
 #' @export
 vis_unicox_tree <- function(Gene = "TP53", measure = "OS", data_type = "mRNA", 
-      threshold = 0.5, values = c("grey", "#E31A1C", "#377DB8"), opt_pancan = .opt_pancan) {
+      values = c("grey", "#E31A1C", "#377DB8"), opt_pancan = .opt_pancan) {
   tcga_surv <- load_data("tcga_surv")
   tcga_gtex <- load_data("tcga_gtex")
 
@@ -254,23 +253,10 @@ vis_unicox_tree <- function(Gene = "TP53", measure = "OS", data_type = "mRNA",
     dplyr::inner_join(tcga_gtex[, c("tissue", "sample")], by = "sample")
   sss <- split(ss, ss$tissue)
   tissues <- names(sss)
-  unicox_res_all_cancers <- purrr::map(tissues, purrr::safely(function(cancer) {
-    # cancer = "ACC"
+  .f = function(cancer) {
     sss_can <- sss[[cancer]]
-    if (threshold == 0.5) {
-      sss_can <- sss_can %>%
-        dplyr::mutate(group = ifelse(.data$values > stats::median(.data$values), "high", "low")) %>%
-        dplyr::mutate(group = factor(.data$group, levels = c("low", "high")))
-    }
-
-    if (threshold == 0.25) {
-      sss_can <- sss_can %>%
-        dplyr::mutate(group = ifelse(.data$values > stats::quantile(.data$values)[4], "high",
-          ifelse(.data$values < stats::quantile(.data$values)[2], "low", "middle")
-        )) %>%
-        dplyr::filter(group != "middle") %>%
-        dplyr::mutate(group = factor(.data$group, levels = c("low", "high")))
-    }
+
+
 
     unicox_res_genes <- ezcox::ezcox(
       sss_can %>%
@@ -285,7 +271,8 @@ vis_unicox_tree <- function(Gene = "TP53", measure = "OS", data_type = "mRNA",
     unicox_res_genes$cancer <- cancer
     unicox_res_genes$measure <- measure
     return(unicox_res_genes)
-  })) %>% magrittr::set_names(tissues)
+  }
+  unicox_res_all_cancers <- purrr::map(tissues, purrr::safely(.f)) %>% magrittr::set_names(tissues)
 
   unicox_res_all_cancers <- unicox_res_all_cancers %>%
     purrr::map(~ .x$result) %>%

R/vis_pcawg_value.R

@@ -213,7 +213,6 @@ vis_pcawg_dist <- function(Gene = "TP53",
 #'
 #' @inheritParams vis_toil_TvsN
 #' @param measure a survival measure, e.g. "OS".
-#' @param threshold a expression cutoff, `0.5` for median.
 #' @param data_type choose gene profile type, including "mRNA","transcript","methylation","miRNA","protein","cnv"
 #' @return a `ggplot` object
 #' @examples
@@ -224,7 +223,7 @@ vis_pcawg_dist <- function(Gene = "TP53",
 
 
 vis_pcawg_unicox_tree <- function(Gene = "TP53", measure = "OS", data_type = "mRNA", 
-  threshold = 0.5, values = c("grey", "#E31A1C", "#377DB8"), opt_pancan = .opt_pancan) {
+  values = c("grey", "#E31A1C", "#377DB8"), opt_pancan = .opt_pancan) {
   pcawg_info <- load_data("pcawg_info")
 
   # t1 <- query_pcawg_pancan_value(Gene, data_type)
@@ -252,21 +251,6 @@ vis_pcawg_unicox_tree <- function(Gene = "TP53", measure = "OS", data_type = "mR
   tissues <- names(sss)
   unicox_res_all_cancers <- purrr::map(tissues, purrr::safely(function(cancer) {
     sss_can <- sss[[cancer]]
-    if (threshold == 0.5) {
-      sss_can <- sss_can %>%
-        dplyr::mutate(group = ifelse(.data$values > stats::median(.data$values), "high", "low")) %>%
-        dplyr::mutate(group = factor(.data$group, levels = c("low", "high")))
-    }
-
-    if (threshold == 0.25) {
-      sss_can <- sss_can %>%
-        dplyr::mutate(group = ifelse(.data$values > stats::quantile(.data$values)[4], "high",
-          ifelse(.data$values < stats::quantile(.data$values)[2], "low", "middle")
-        )) %>%
-        dplyr::filter(group != "middle") %>%
-        dplyr::mutate(group = factor(.data$group, levels = c("low", "high")))
-    }
-
 
     unicox_res_genes <- ezcox::ezcox(
       sss_can,

inst/shinyapp/modules/02_quick/modules-1-tcga-10-Cox.R

@@ -105,7 +105,6 @@ server.modules_1_tcga_10 = function(input, output, session){
         p <- vis_unicox_tree(
             Gene = mol_info$molecule(),
             measure = input$measure,
-            threshold = 0.5,
             data_type = mol_info$profile(),
             values = c(input$first_col, input$second_col, input$third_col)
         )

inst/shinyapp/modules/02_quick/modules-2-pcawg-04-Cox.R

@@ -96,7 +96,6 @@ server.modules_2_pcawg_04 = function(input, output, session){
         p <- vis_pcawg_unicox_tree(
             Gene = mol_info$molecule(),
             measure = "OS",
-            threshold = 0.5,
             data_type = mol_info$profile(),
             values = c(input$first_col, input$second_col, input$third_col)
         )

vignettes/api.Rmd

@@ -121,7 +121,6 @@ if (require("gganatogram")) {
 vis_unicox_tree(
   Gene = "TP53",
   measure = "OS",
-  threshold = 0.5,
   values = c("grey", "#E31A1C", "#377DB8")
 )
 ```